An Introduction to Feature Extraction

By Isabelle M Guyon, Andre´ Elisseeﬀ. 2006

602 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

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Citations in the corpus

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines (2018, neutral): “Feature extraction [28].”
A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications (2020, methodology): “ is pertinent to preprocess data sample to extract the certain features or attributes that represent the most characteristic pieces of information. This process is referred to as “feature extraction” [78]. Next, the processed data samples, which are expressed in extracted feature terms, are used to ”
Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors (2014, background): “Feature extraction is the process by which relevant characteristics or attributes are identified from the collected data [17].”
A review of feature selection methods based on mutual information (2013, methodology): “lity. In probability the measure of suﬃcient feature subset can be expressed as the expected value over p(F) of the Kullback-Leibler divergence between p(C|F)and p(C|S)[33]. According to Guyon et al. [24], this can be expressed in terms of MI as follows: DMI(S)=I(F;C)−I(S;C). (18) Guyon et al. [24] ”
ECG Classification Using Wavelet Packet Entropy and Random Forests (2016, background): “The features are expected to contain the relevant information from the input data, so that the desired task can be performed by using this reduced representation instead of the complete initial data [45,46].”
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks (2019, methodology): “, xN }, a pair of popular methods has been conceived for revealing the underlying unknown features of N input data, namely density estimation [53] as well as feature extraction [54].”